We propose a random network model incorporating heterogeneity of agents and a continuous notion of homophily. Unlike … positive level of homophily our model exhibits clustering, that is an increased probability of linkage given a common neighbor … new employee via the social network. …

payoffs depend on the social distance between them. We characterize the clustering coefficient and average path length in … distributions, positive assortativity of degrees, and clustering-degree correlation. …

The communities in a network have distinct characteristics and interrelationships. Community discovery methods based on … node embedding and deep learning have surpassed spectral clustering and statistical inference as the preferred methods for … handling high-dimensional network data. Community detection in graph networks using graph neural networks (GNNs) is a rapidly …